Adding conditional branching operation to SNQL For Sensor Database

Lim, Chong Sok; Lim, Jaehyoung; Hyun, Soon J.

doi:10.1109/icsai.2012.6223289

Cited by 1 publication

(15 citation statements)

References 12 publications

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“…In this section, the spatial operators of SNQL + are introduced, by extending the previous SNQL [8,14] to support various space operations. A geometric target space in SNQL + is represented by a rectangle called a SNQL + envelope as the basic unit for spatial query operation.…”

Section: Design Of Snqlmentioning

confidence: 99%

“…In this section, SNQL + is introduced, which extends SNQL (Sensor Network Query Language) [8,14] to be able to support the spatial operators. The original SNQL was designed based on SELECT-FROM-WHERE structure and supports instant queries, continuous queries, and event-based queries.…”

Section: Spatial Expressions In Snqlmentioning

confidence: 99%

“…Sensor Network Query Language (SNQL) and its query processor use SQL-like language structure and various query processing functions running over Android [8,14]. It is designed to support instant queries, continuous queries, and event-based queries.…”

Section: Related Workmentioning

confidence: 99%

“…(i) We have extended our previous work on sensor network query language SNQL [8,14] by incorporating various spatial operators, so that more sophisticated expressions of target space are made possible in our new system called SNQL + .…”

Section: Introductionmentioning

confidence: 99%

“…This paper presents our design and implementation of spatial operations and associated query processing algorithm in an effort to better support sophisticated demands of sensor network applications. We have designed spatial operators based on geometric parameters, such as Envelope, Nearby, Distance, and Direction, as well as binary spatial operators, such as Intersection, Union, and Difference in an attempt to extend our previous sensor network database SNQL [8,14]. We also have developed our query processing method called LCA-based in-network query processing (in short, LCA-algorithm).…”

Section: Introductionmentioning

confidence: 99%

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Design and Implementation of Spatial Operators and Energy-Efficient Query Processing Strategy in Wireless Sensor Network Database System

Lim

Lee

Park

et al. 2015

International Journal of Distributed Sensor Networks

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Database applications in wireless sensor networks very often demand data collection from sensor nodes of specific target regions. Design and development of spatial query expressions and energy-efficient query processing strategy are important issues for sensor network database systems. The existing sensor network database systems lack the needed sophistication for the space calculation of the target sensor nodes; hence, unnecessary query/data transmissions are required between the sensor nodes and the server. This paper describes our spatial operations and energy-efficient query processing methods that are designed and implemented in our sensor network database system called SNQL + . With a set of spatial operators based on geometric parameters, such as Envelope, NearBy, Distance, Direction, and set theoretic operators, SNQL + allows sensor network applications to easily specify the target space of interest. Our energy-efficient query processing strategy implements an in-network query management based on the lowest common ancestor (LCA) algorithm, so that the query processing cost for calculating the target spaces is greatly reduced by avoiding the need of heavy query/data transmissions between the base-station and target nodes. Performance evaluation shows that our proposed design and implementation of spatial query expressions and processing strategy achieve improved energy efficiency for database operations in the wireless sensor network.

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Section: Design Of Snqlmentioning

confidence: 99%

Section: Spatial Expressions In Snqlmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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